Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects malicious OAuth 2.0 device authorization grant requests directed at Microsoft services. This rule identifies usage of specific App IDs associated with the Microsoft Authentication Broker combined with the 'offline_access' Graph scope, a pattern indicative of GhostCode-style phishing campaigns designed to steal access and refresh tokens.
Detects repeated polling activity against a suspected device code endpoint, common in OAuth 2.0 device authorization grant phishing attacks where an adversary attempts to maintain session persistence or status checks for a stolen device code.
This rule detects activities associated with the GhostCode phishing kit, which leverages a device-code phishing flow. It identifies malicious URLs interacting with harvester APIs to retrieve codes, email-delivered lures containing specific phishing markers ('userCodeDisplay', 'Verified Enterprise'), and corresponding endpoint/browser telemetry showing the rendered phishing page elements.
This rule monitors network connections, DNS resolutions, and email URLs to detect traffic communicating with a known adversary-in-the-middle (AiTM) phishing infrastructure panel. By correlating security logs, DNS events, and email URL data against this specific indicator of compromise, it identifies potential interaction with phishing sites designed to capture credentials or session tokens.
Detects interaction with known infrastructure associated with the PREY-0058 campaign, which utilizes Adversary-in-the-Middle (AiTM) phishing lures mimicking passkey or MFA registration pages to target Microsoft 365 and other SaaS applications.
This rule detects network traffic indicative of the PEEP Browser RAT, specifically HTTP beacons targeting the URI path '/api/commands'. It monitors for unique HTTP headers ('X-PEEP-Agent-Id', 'X-PEEP-Agent-Key') and connections to known malicious infrastructure.
Detects DNS queries for lookalike domains combining a government/brand-impersonation keyword (as its own label, not a substring) with a disposable TLD used across the IronToll campaign. Dropped the standalone 'digital' keyword, which was generic enough to match ordinary e-commerce domains on the same TLDs.
Detects anomalous network traffic patterns characterized by rapid domain rotation, where multiple distinct domains resolve to a known set of IronToll C2 infrastructure IP addresses within a short timeframe (48 hours). Added an explicit 2-day lookback window — the original query had no time bound at all, so every scheduled run re-scanned the table's entire retention period and would keep re-surfacing the same historical match indefinitely instead of only genuinely recent activity.
Detects anomalous network traffic patterns characterized by rapid domain rotation, where multiple distinct domains resolve to a known set of IronToll C2 infrastructure IP addresses within a short timeframe (48 hours). Added an explicit 2-day lookback window — the original query had no time bound at all, so every scheduled run re-scanned the table's entire retention period and would keep re-surfacing the same historical match indefinitely instead of only genuinely recent activity.
Detects anomalous network traffic patterns characterized by rapid domain rotation, where multiple distinct domains resolve to a known set of IronToll C2 infrastructure IP addresses within a short timeframe (48 hours). Added an explicit 2-day lookback window — the original query had no time bound at all, so every scheduled run re-scanned the table's entire retention period and would keep re-surfacing the same historical match indefinitely instead of only genuinely recent activity.
Detects anomalous network traffic patterns characterized by rapid domain rotation, where multiple distinct domains resolve to a known set of IronToll C2 infrastructure IP addresses within a short timeframe (48 hours). Added an explicit 2-day lookback window — the original query had no time bound at all, so every scheduled run re-scanned the table's entire retention period and would keep re-surfacing the same historical match indefinitely instead of only genuinely recent activity.
Detects country-coded lure path requests (/eg, /ma) followed by a cloaking differential response (desktop UA blocked with 404, mobile UA served content). Fixed a regex bug where the original pattern matched any path merely starting with 'eg' or 'ma' (e.g. /egg.jpg, /mail, /manifest.json) instead of the exact path segment.
Detects the Iron Man System phishing kit via its HTTP fingerprint: a request-header rule (ETag/Server/Via combo) checked on the external server's response, and three request-side rules checking for the kit's hashed asset paths and favicon when an internal host requests them from an external site. Fixed a direction bug on the three request-side rules that had source/destination reversed (they previously required an external host to request the path from an internal server, which would rarely if ever fire).
Detects successful VPN authentication attempts originating from known Cloudflare WARP tunnel infrastructure or European VPS provider IP address ranges. This pattern is often used by adversaries to mask their true geographic origin or bypass location-based security policies.
This rule detects DNS queries for the hardcoded domain 'gsx.uk.com', which is associated with the command-and-control (C2) infrastructure of BabylonRAT malware.
This rule detects DNS queries for the hardcoded domain 'gsx.uk.com', which is associated with the command-and-control (C2) infrastructure of BabylonRAT malware.
This rule detects DNS queries for the hardcoded domain 'gsx.uk.com', which is associated with the command-and-control (C2) infrastructure of BabylonRAT malware.
This rule detects DNS queries for the hardcoded domain 'gsx.uk.com', which is associated with the command-and-control (C2) infrastructure of BabylonRAT malware.
CloudSEK researchers uncovered BigBear 2.0, a global Microsoft 365 phishing-as-a-service operation targeting hundreds of organizations across 40+ countries. The investigation exposed the attacker’s admin panel, affiliate network, phishing infrastructure, and thousands of stolen credentials and session cookies, revealing how modern AiTM attacks can hijack authenticated sessions even after MFA.
Detects network connections to known command and control (C2) infrastructure, including hardcoded malicious domains, specific C2 IP addresses, and suspicious GitHub access patterns by processes other than standard web browsers, which may indicate malicious ingress tool transfer or C2 communication.
This rule detects potentially malicious behavior by correlating intensive usage of graphics-related API calls (like BitBlt, GetDC, etc.) which are indicative of screen capture, with the execution of specific command identifiers typically associated with C2 (Command and Control) traffic. The combination suggests an adversary is capturing screen data and potentially staging or exfiltrating it via a C2 channel.
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